The objective of the proposed study is to evaluate the chronic respiratory effects of on-the-job exposure to toxic contaminants among firefighters. A follow-up study of a cohort (N=961) of Baltimore City firefighters will be conducted. Data collected 6 to 9 years ago on pulmonary function, respiratory symptoms, and smoking habits are available. All men who are alive and live in Maryland will be asked to participate. Each eligible man will be sent an introductory letter to explain the objectives of the study and the procedures involved. Voluntary participation will be sought. In-active men will be contacted by telephone to determine a date and fire department location for data collection. Active men will be visited at the location of their current fire department assignment. On the pre-scheduled date, each man will be asked to sign an informed consent statement. In addition to explaining the objectives and procedures, permission to review infirmary records will be requested. All participants will perform a pulmonary function test under the direction of a trained technician. FEV1, FVC, and MMEF will be calculated. Each man will also be asked to complete a self-administered questionaire about respiratory symptoms, medical history, work history, and smoking habits. Attendance records, infirmary files, company journals, and fire cards will be reviewed and appropriate data abstracted. Rates of pulmonary function change, incidence and remission of respiratory symptoms, and of illness absences will be calculated. The prevalence of chronic bronchitis and of obstructive airways disease will be determined. The relationship between both baseline function and symptoms and subsequent transfers and early retirement will be examined. Pulmonary function and respiratory symptom data on firefighters will be compared to similar data available from a Baltimore area general population comparison series. Univariate statistical techniques will be used to identify factors that are associated with each health outcome in firefighters. Multiple linear regression will be used to assess the importance of occupational factors.